Abstract:
Systems, methods, apparatuses, and computer readable media are disclosed for providing analytics using real time data on movement and proximity of tagged objects for determining play models and outputting events. In one embodiment, a method is provided for determining play data that at least includes correlating at least one tag to a participant; receiving blink data transmitted by the at least one tag; and determining tag location data based on the blink data. The method further includes receiving participant role data; comparing the tag location data to participant dynamics/kinetics models based at least in part on the participant role data; determining participant location data based on the comparing the tag location data to the participant dynamics/kinetics models.
Abstract:
Systems, methods, apparatuses, and computer readable media are disclosed for providing performance modeling by combining tags and sensors providing real time data on movement and proximity of tagged objects. In one embodiment, a method is provided for monitoring a participant that at least includes correlating at least one tag to the participant; receiving blink data transmitted by the at least one tag; determining tag location data based on the blink data; correlating a sensor to the participant; and receiving sensor derived data. The method further includes receiving participant role data; comparing the tag location data to participant dynamics/kinetics models based at least in part on the participant role data; and determining the participant location data based on comparing the tag location data and the sensor derived data to the participant dynamics/kinetics models.
Abstract:
Systems, methods, apparatuses, and computer readable media are disclosed for providing analytics using real time data on movement and proximity of tagged objects for determining location based on participant dynamics/kinetics models. In one embodiment, a method is provided for monitoring a participant that at least includes correlating at least one tag to the participant; receiving blink data transmitted by the at least one tag; and determining tag location data based on the blink data. The method further includes receiving participant role data; comparing the tag location data to participant dynamics/kinetics models based at least in part on the participant role data; and determining participant location data based on the comparing the tag location data to the participant dynamics/kinetics models.
Abstract:
Systems, methods, apparatuses, and computer readable media are disclosed for providing performance modeling by combining tags and sensors providing real time data on movement and proximity of tagged objects. In one embodiment, a method is provided for monitoring a participant that at least includes correlating at least one tag to the participant; receiving blink data transmitted by the at least one tag; determining tag location data based on the blink data; correlating a sensor to the participant; and receiving sensor derived data. The method further includes receiving participant role data; comparing the tag location data to participant dynamics/kinetics models based at least in part on the participant role data; and determining the participant location data based on comparing the tag location data and the sensor derived data to the participant dynamics/kinetics models.
Abstract:
Systems, methods, apparatuses, and computer readable media are disclosed for providing analytics for evaluating performance using real time data on movement and proximity of tagged objects. In one embodiment, a method is provided for evaluating a player that includes correlating at least one tag to the player; receiving blink data transmitted by the at least one tag; and determining tag location data based on the blink data. The method further includes receiving player role data; comparing the tag location data to player dynamics/kinetics models based at least in part on the player role data; determining player location data based on the comparing the tag location data to the player dynamics/kinetics models; and determining player performance information based on comparing the player location data to stored player location data.
Abstract:
Systems, methods, apparatuses, and computer readable media are disclosed for over-determining location estimations for an asset based on location estimates from a plurality of tags. Examples employ a spatial association model in a location system. Examples include a method for processing location information received from a radio frequency (RF) location tag. The method includes determining a first location of a first RF location tag associated with an asset, determining at least one second location of at least one second RF location tag associated with the asset, determining, using a processor, that the first location is not a valid location based at least in part on a comparison of the first location with the at least one second location using a spatial association model associated with the asset, and identifying the first location as erroneous in response to determining that the first location is not a valid location.
Abstract:
Systems, methods, apparatuses, and computer readable media are disclosed for determining events and outputting events based on real-time data for location and movement of objects and audio data. In one embodiment, a method is provided for a method of determining play events that at least includes receiving audio data, wherein the audio data is received from at least one of a memory or a sensor; determining an event probability based on comparing the audio data to an audio profile; and generating an event based on the event probability satisfying a predetermined threshold.
Abstract:
Provided herein are systems and computer readable media for associating environmental measurements with an individual using a plurality of sensors, a plurality of tags and a plurality of receivers disposed about a monitored area. Various embodiments of the invention include: receiving blink data from receivers positioned about the monitored area, wherein the blink data is generated by at least one tag carried by the individual; determining tag location data based on the blink data, wherein the tag location data comprises a tag location estimate; associating the tag location data with an individual profile; receiving a sensor signal from a sensor comprising environmental measurements associated with the individual; receiving a sensor location associated with the sensor; comparing the tag location estimate to the sensor location; determining a sensor-individual correlator based on the proximity between the tag location estimate and the sensor location; and associating the sensor-individual correlator with the environmental measurements.
Abstract:
A method, apparatus and computer program product are provided for collecting sporting event data based on real time data for proximity and movement of objects. In the context of a method, the method includes calculating a tag data filter parameter for a plurality of tag events based on received tag blink data and tag location data, wherein the tag data filter parameter comprises a blink period, distance span, or velocity, calculating a participant location data adjustment factor based on the tag data filter parameter, and calculating multidimensional player location information per unit time based on the plurality of tag events and the participant location adjustment factor.
Abstract:
Systems, methods, apparatuses, and computer readable media are disclosed for providing analytics using real time data on movement and proximity of tagged objects for determining play models and outputting events. In one embodiment, a method is provided for determining play data that at least includes correlating at least one tag to a participant; receiving blink data transmitted by the at least one tag; and determining tag location data based on the blink data. The method further includes receiving participant role data; comparing the tag location data to participant dynamics/kinetics models based at least in part on the participant role data; determining participant location data based on the comparing the tag location data to the participant dynamics/kinetics models. The method further includes receiving field data; comparing the participant location data to formation models based at least in part on the participant role data and the field data; and determining formation data based on the comparing the participant location data to the formation models. The method further includes comparing the formation data and participant location data to play models; and determining play data based on the comparing the formation data and participant location data to the play models.